Team:Nantes/Contribution
iGEM x COVID-19
When the team was formed in February, we were all in the same university, and most of us in our last year of our bachelor's degrees. We knew that when the next school year starts a lot of the members are not going to be in the same city as us for their masters. It is often the same every year, as shown by the survey carried out with last year's team. We had more than enough time to find an organization plan for the last few months of the iGEM competition which are usually the most stressful ones and demand a lot of time and effort. What we did not expect though was a lockdown because of the pandemic.
This is why this year our team decided to make a contribution a bit specific to the current situation. COVID-19 hit us unexpectedly and it was not easy to adapt. We were all on lockdown for 2 months and even after that meeting in real life was not advised. Deciding to continue the project and the competition needed adjustments. Having to work together and despite the distance demands effort, extra time and being able to adapt. When we see what is happening around the world and how the pandemic is progressing it is more than clear that it would not end soon.
Newly formed teams for iGEM 2021 could benefit from the documents you will find on this page. You will have access to some organisation plans, some suggestions and a few tips on how to work together without actually being together
This is why this year our team decided to make a contribution a bit specific to the current situation. COVID-19 hit us unexpectedly and it was not easy to adapt. We were all on lockdown for 2 months and even after that meeting in real life was not advised. Deciding to continue the project and the competition needed adjustments. Having to work together and despite the distance demands effort, extra time and being able to adapt. When we see what is happening around the world and how the pandemic is progressing it is more than clear that it would not end soon.
Newly formed teams for iGEM 2021 could benefit from the documents you will find on this page. You will have access to some organisation plans, some suggestions and a few tips on how to work together without actually being together
Scientific Contribution
In most cases, regulation of translation in bacteria is reported to occur mainly during the initiation [1]. The Ribosome binding site (RBS) is a key element controlling this step and thus is an important component to consider during the genetic design. This small sequence in the mRNA is highly sensitive to its associated nucleotide context. The accessibility of the RBS and its ability to trigger translation have been studied and have allowed the creation of a biophysical model [2][3][4][5] available as a web interface at :
https://www.denovodna.com/software/
This tool, like any model, has some limits and is reported to be accurate within a range of 2.3 errors [2]. Nevertheless, this tool allows us to get some really interesting insights for the genetic design. It is indeed precise enough to get a good idea of the translation rate’s orders of magnitude. We used this tool to analyze the part of a previous iGEM team: BBa_K2613743. This part consists of two coding sequences under the control of one unique promoter. As mentioned in the team’s wiki: the team was unable to see the expression of the His-tagged protein AgrB.
In our analysis, we used the sequence right after the end of the annotated promoter as the polycistronic mRNA. The model predicts a strength of 132.2 a.u. for the first RBS (position +18). It is really low and cannot be distinguished from the noise, which is here the other very low alternative start codon found in the sequence. As a comparison, the second coding sequence using the exact same RBS is predicted to have a translation rate of over 10000 a.u (position +681). In this case, for the same mRNA, the part BBa_B0034 seems to be highly impacted by the context.
As an example, we found in the literature the case of a lab [6] which designed what they considered as a low RBS with a strength of 9500 a.u. and a strong RBS with a strength of 95000 a.u. Therefore, we can assume that a 132.2 a.u. translation rate is too weak to get a correct initiation and can partially explain the lack of induced protein.
This hypothesis is only based on in-silico insights and must be tested in vivo in order to be validated or rejected. To do so, future teams interested in this part should try to detect the His-tagged protein by using a stronger RBS. We used the RBS calculator in our genetic design and with the example above we recommend the use of this tool to control the expression level of an existing part or to predict the translation rate of a new one.
https://www.denovodna.com/software/
This tool, like any model, has some limits and is reported to be accurate within a range of 2.3 errors [2]. Nevertheless, this tool allows us to get some really interesting insights for the genetic design. It is indeed precise enough to get a good idea of the translation rate’s orders of magnitude. We used this tool to analyze the part of a previous iGEM team: BBa_K2613743. This part consists of two coding sequences under the control of one unique promoter. As mentioned in the team’s wiki: the team was unable to see the expression of the His-tagged protein AgrB.
In our analysis, we used the sequence right after the end of the annotated promoter as the polycistronic mRNA. The model predicts a strength of 132.2 a.u. for the first RBS (position +18). It is really low and cannot be distinguished from the noise, which is here the other very low alternative start codon found in the sequence. As a comparison, the second coding sequence using the exact same RBS is predicted to have a translation rate of over 10000 a.u (position +681). In this case, for the same mRNA, the part BBa_B0034 seems to be highly impacted by the context.
As an example, we found in the literature the case of a lab [6] which designed what they considered as a low RBS with a strength of 9500 a.u. and a strong RBS with a strength of 95000 a.u. Therefore, we can assume that a 132.2 a.u. translation rate is too weak to get a correct initiation and can partially explain the lack of induced protein.
This hypothesis is only based on in-silico insights and must be tested in vivo in order to be validated or rejected. To do so, future teams interested in this part should try to detect the His-tagged protein by using a stronger RBS. We used the RBS calculator in our genetic design and with the example above we recommend the use of this tool to control the expression level of an existing part or to predict the translation rate of a new one.
References
[1] Laursen, B. S., Sorensen, H. P., Mortensen, K. K., & Sperling-Petersen, H. U. (2005). Initiation of Protein Synthesis in Bacteria. Microbiology and Molecular Biology Reviews, 69(1), 101–123.
[2] Salis, H. M., Mirsky, E. A., & Voigt, C. A. (2009). Automated design of synthetic ribosome binding sites to control protein expression. Nature Biotechnology, 27(10), 946–950.
[3] Espah Borujeni, A., Cetnar, D., Farasat, I., Smith, A., Lundgren, N., & Salis, H. M. (2017). Precise quantification of translation inhibition by mRNA structures that overlap with the ribosomal footprint in N-terminal coding sequences. Nucleic Acids Research, 45(9), 5437–5448.
[4] Espah Borujeni, A., Channarasappa, A. S., & Salis, H. M. (2013). Translation rate is controlled by coupled trade-offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites. Nucleic Acids Research, 42(4), 2646–2659.
[5] Espah Borujeni, A., & Salis, H. M. (2016). Translation Initiation is Controlled by RNA Folding Kinetics via a Ribosome Drafting Mechanism. Journal of the American Chemical Society, 138(22), 7016–7023.
[6] Ceroni, F., Algar, R., Stan, G.-B., & Ellis, T. (2015). Quantifying cellular capacity identifies gene expression designs with reduced burden. Nature Methods, 12(5), 415–418.
[1] Laursen, B. S., Sorensen, H. P., Mortensen, K. K., & Sperling-Petersen, H. U. (2005). Initiation of Protein Synthesis in Bacteria. Microbiology and Molecular Biology Reviews, 69(1), 101–123.
[2] Salis, H. M., Mirsky, E. A., & Voigt, C. A. (2009). Automated design of synthetic ribosome binding sites to control protein expression. Nature Biotechnology, 27(10), 946–950.
[3] Espah Borujeni, A., Cetnar, D., Farasat, I., Smith, A., Lundgren, N., & Salis, H. M. (2017). Precise quantification of translation inhibition by mRNA structures that overlap with the ribosomal footprint in N-terminal coding sequences. Nucleic Acids Research, 45(9), 5437–5448.
[4] Espah Borujeni, A., Channarasappa, A. S., & Salis, H. M. (2013). Translation rate is controlled by coupled trade-offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites. Nucleic Acids Research, 42(4), 2646–2659.
[5] Espah Borujeni, A., & Salis, H. M. (2016). Translation Initiation is Controlled by RNA Folding Kinetics via a Ribosome Drafting Mechanism. Journal of the American Chemical Society, 138(22), 7016–7023.
[6] Ceroni, F., Algar, R., Stan, G.-B., & Ellis, T. (2015). Quantifying cellular capacity identifies gene expression designs with reduced burden. Nature Methods, 12(5), 415–418.
igemnantes2020@gmail.com